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Computer Science > Computer Vision and Pattern Recognition

arXiv:2309.06188 (cs)
[Submitted on 12 Sep 2023 (v1), last revised 12 Oct 2023 (this version, v2)]

Title:Computer Vision Pipeline for Automated Antarctic Krill Analysis

Authors:Mazvydas Gudelis, Michal Mackiewicz, Julie Bremner, Sophie Fielding
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Abstract:British Antarctic Survey (BAS) researchers launch annual expeditions to the Antarctic in order to estimate Antarctic Krill biomass and assess the change from previous years. These comparisons provide insight into the effects of the current environment on this key component of the marine food chain. In this work we have developed tools for automating the data collection and analysis process, using web-based image annotation tools and deep learning image classification and regression models. We achieve highly accurate krill instance segmentation results with an average 77.28% AP score, as well as separate maturity stage and length estimation of krill specimens with 62.99% accuracy and a 1.98mm length error respectively.
Comments: Accepted to MVEO @ BMVC 2023
Subjects: Computer Vision and Pattern Recognition (cs.CV)
Cite as: arXiv:2309.06188 [cs.CV]
  (or arXiv:2309.06188v2 [cs.CV] for this version)
  https://doi.org/10.48550/arXiv.2309.06188

Submission history

From: Mazvydas Gudelis [view email]
[v1] Tue, 12 Sep 2023 12:54:12 UTC (22,231 KB)
[v2] Thu, 12 Oct 2023 11:51:21 UTC (22,232 KB)
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